COSMO-SkyMed an existing opportunity for observing the Earth

Covello, Fabio; Battazza, Fabrizio; Coletta, Alessandro; Lopinto, E.; Fiorentino, Claudia A.; Pietranera, L.; Valentini, G.; Zoffoli, Simona

doi:10.1016/j.jog.2010.01.001

Cited by 209 publications

(113 citation statements)

References 2 publications

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“…Given the short revisiting time of modern satellites (ASI 2007;Covello et al 2010), the update rate of the InSARderived susceptibility maps could potentially be significantly higher than that of maps solely based on field surveys. A higher temporal resolution will also permit to improve the identification of the nonlinear components of ground deformation, i.e., accelerating and decelerating events (Herrera et al 2011).…”

Section: Discussionmentioning

confidence: 99%

“…Indeed, the use of spaceborne radar measures has proven over time to be a reliable source to improve landslide and subsidence identification and characterization (Metternicht et al 2005;Strozzi et al 2005;Farina et al 2007;Righini et al 2008;Cigna et al 2011;Raspini et al 2013;Tofani et al 2013). The possibility to monitor the ground deformation even in remote areas, the short revisiting time of the Cosmo satellite constellation (16 days in standard orbit cycle mode; ASI 2007 andCovello et al 2010) and the release of the new SqueeSAR algorithm, which guarantees a remarkable increase in detectable measuring points, are key features in helping to overcome some of the aforementioned issues.…”

Section: Introductionmentioning

confidence: 99%

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A simple method to help determine landslide susceptibility from spaceborne InSAR data: the Montescaglioso case study

2016

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On December 3, 2013, a large complex landslide was triggered SW of the town of Montescaglioso (Southern Italy), causing the destruction of roads, commercial buildings and private dwellings, as well as several direct and indirect economic losses. A set of interferometric ground measurements acquired by the Cosmo-SkyMed satellite constellation and processed by means of the SqueeSAR algorithm was used to study the pre-event slope displacements in the entire Montescaglioso municipal area. Data span from January 30, 2012, to December 2, 2013, and show average line-of-sight velocities of 1-10 mm/year in the slope sector ultimately affected by the collapse. In retrospect, a time series analysis of the radar targets was performed in order to identify and characterize all the slope instabilities in proximity of the town. This was based on the setup of characteristic thresholds of displacement. The procedure permitted to locate several areas which recurrently exceeded these previously established thresholds, in consistency with the amount of precipitation. In particular, the major source of potential hazard in the area was indeed found where the December 3, 2013, landslide eventually occurred. The results of this quick data processing technique were validated through comparison with two independently developed landslide maps. This simple method, which is not supposed to diminish the importance of geomorphologic field surveys, could improve both the accuracy and the update rate of landslide susceptibility maps.Not relying on arbitrary or empirically derived approaches, it has the advantage of computing statistically based thresholds specific for each time series. By indicating the slope sectors in higher need of deeper in situ investigation, more support could be provided to administrative bodies for the processes of risk assessment and management.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A simple method to help determine landslide susceptibility from spaceborne InSAR data: the Montescaglioso case study

2016

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“…COSMO-SkyMed (the acronym CSK will be also used hereafter) is a cooperation project between the Italian Space Agency (ASI) and the Italian Defence Ministry which has been developed to provide users with fast, meter level-resolution, all-weather X-band SAR data for disaster management. With the full constellation of four satellites deployed (the fourth satellite was launched on 5 November 2010), the revisit time will be 12 h in the worst case (Covello et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

An algorithm for operational flood mapping from Synthetic Aperture Radar (SAR) data using fuzzy logic

Pulvirenti

Pierdicca

Chini

et al. 2011

Nat. Hazards Earth Syst. Sci.

234

140

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Abstract. An algorithm developed to map flooded areas from synthetic aperture radar imagery is presented in this paper. It is conceived to be inserted in the operational flood management system of the Italian Civil Protection and can be used in an almost automatic mode or in an interactive mode, depending on the user's needs. The approach is based on the fuzzy logic that is used to integrate theoretical knowledge about the radar return from inundated areas taken into account by means of three electromagnetic scattering models, with simple hydraulic considerations and contextual information. This integration aims at allowing a user to cope with situations, such as the presence of vegetation in the flooded area, in which inundation mapping from satellite radars represents a difficult task. The algorithm is designed to work with radar data at L, C, and X frequency bands and employs also ancillary data, such as a land cover map and a digital elevation model. The flood mapping procedure is tested on an inundation that occurred in Albania on January 2010 using COSMO-SkyMed very high resolution X-band SAR data.

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“…The first dataset is composed of 35 SAR images, collected by the C-band ASAR/ENVISAT sensor [49], from 26 February 2007 to 13 September 2010 (ascending passes, VV polarization, Track 497, Frame 616, swath IS2, with a sensor side-looking and a satellite heading angle of about 23 • and 12 • , respectively). The second dataset consists of 61 SAR scenes acquired by the SAR sensors of the X-band COSMO-SkyMed (CSK) satellites constellation [50], from 7 December 2013 to 18 March 2016 (descending passes, HH polarization, with a side-looking angle of about 29 • and a satellite heading angle of about 8 • ). As is evident, the two available SAR datasets are not time-overlapping, and there is a long temporal gap (of about three years) between the two relevant groups of images.…”

Section: Sar Datamentioning

confidence: 99%

The Use of C-/X-Band Time-Gapped SAR Data and Geotechnical Models for the Study of Shanghai’s Ocean-Reclaimed Lands through the SBAS-DInSAR Technique

et al. 2016

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Abstract:In this work, we investigate the temporal evolution of ground deformation affecting the ocean-reclaimed lands of the Shanghai (China) megacity, from 2007 to 2016, by applying the Differential Synthetic Aperture Radar Interferometry (DInSAR) technique known as the Small BAseline Subset (SBAS) algorithm. For the analysis, we exploited two sets of non-time-overlapped synthetic aperture radar (SAR) data, acquired from 2007 to 2010, by the ASAR/ENVISAT (C-band) instrument, and from 2014 to 2016 by the X-band COSMO-SkyMed (CSK) sensors. The long time gap (of about three years) existing between the available C-and X-band datasets made the generation of unique displacement time-series more difficult. Nonetheless, this problem was successfully solved by benefiting from knowledge of time-dependent geotechnical models, which describe the temporal evolution of the expected deformation affecting Shanghai's ocean-reclaimed platforms. The combined ENVISAT/CSK (vertical) deformation time-series were analyzed to gain insight into the future evolution of displacement signals within the investigated area. As an outcome, we find that ocean-reclaimed lands in Shanghai experienced, between 2007 and 2016, average cumulative (vertical) displacements extending down to 25 centimeters.

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COSMO-SkyMed an existing opportunity for observing the Earth

Cited by 209 publications

References 2 publications

A simple method to help determine landslide susceptibility from spaceborne InSAR data: the Montescaglioso case study

A simple method to help determine landslide susceptibility from spaceborne InSAR data: the Montescaglioso case study

An algorithm for operational flood mapping from Synthetic Aperture Radar (SAR) data using fuzzy logic

The Use of C-/X-Band Time-Gapped SAR Data and Geotechnical Models for the Study of Shanghai’s Ocean-Reclaimed Lands through the SBAS-DInSAR Technique

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